It is generally known that heart movements during CT imaging cause the recorded data to be inconsistent and also lead to image artifacts which severely restrict the clinical usefulness of the data. In order to prevent such image artifacts, in modern CT cardiac imaging, phase-related representation of the heart is generated by the recording and use of cardiac phase-related data. In this context, there are fundamentally a retrospective acquisition scheme and a prospective acquisition scheme. In the prospective acquisition scheme, only data gathered in a specific window around the rest phase of the heart are recorded and used for image reconstruction. The common aim of these approaches is effectively to freeze the motion of the heart, in order to minimize data inconsistency and thereby to maximize the image quality.
However, with a gantry rotation which is too slow relative to the heart motion or with a heartbeat which is too fast relative to the gantry motion, such strategies are not sufficient to achieve a high enough temporal resolution for calculating an artifact-free image. A variety of algorithms for improving the temporal resolution retrospectively is known in the prior art.
The publication by H. Schöndube, T. Allmendinger, K. Stierstorfer, H. Bruder, and T. Flohr entitled “Evaluation of a novel CT image reconstruction algorithm with enhanced temporal resolution” in: Proceedings of SPIE, p. 79611 N, 2011, describes a reduction in the data quantity required by undershooting the theoretical angular sampling of 180°, wherein due to the incomplete data, the image quality has to be optimized iteratively.
Furthermore, the publication by D. Schafer, J. Borgert, V. Rasche, and M. Grass entitled “Motion-Compensated and Gated Cone Beam Filtered Back-Projection for 3-D Rotational X-Ray Angiography”, in IEEE Transactions on Medical Imaging, Vol. 25, No. 7, pp. 898-906, July 2006, discloses that with known object motion of the data used for reconstruction, said motion can be taken into account during a motion-compensated reconstruction. This procedure leads to a significant improvement in image quality.
Finally, reference is made to the document DE 10 2009 007 236 A1 in which a motion-compensated CT-reconstruction method for an at least partially moving object is disclosed. In this method, the moving object under investigation is scanned with a CT system and sectional images of the object under investigation are computed, with the recorded detector data using an iterative algorithm, wherein the iterative algorithm takes account of motion information concerning the motion of the object under investigation during data recording. This motion information is represented in the form of a motion field comprising a large number of location-specific vectors which describe the motion or the displacement of the object at the respective location at the time point of the recording. For determination of the motion field, it is proposed that two chronologically separated CT images are compared in order, from the change in the CT images, to deduce the location-specific motion.
So far unsolved in this regard, however, is the problem of correctly estimating the motion in order to improve the image quality of the “best-phase” image, that is, the image from a phase of optimum rest and therefore of the highest quality. Previous approaches merely estimate the movement by registering two 3-D standard reconstructions of different heart phases. However, so far, no improvement in the quality of the “best phase” image has been achieved, since such improvement inherently restricts the temporal resolution of the registered data. On the other hand, the images of poorer cardiac phases have been significantly improved with the result, for example, that the imaging of a different cardiac phase with improved image quality is made possible.